Kalman Filtering: with Real-Time Applications (Springer Series in Information Sciences, 17)

Chui, Charles K.; Chen, Guanrong

ISBN 10: 354054013X / ISBN 13: 9783540540137

Published by Springer, 1991

About this Item

Zustand: Sehr gut - Gepflegter, sauberer Zustand. 2. Auflage. Außen: angestoßen. Innen: geknickt. Aus der Auflösung einer renommierten Bibliothek. Kann Stempel beinhalten. | Seiten: 211 | Sprache: Englisch | Produktart: Sonstiges. Seller Inventory # 42663771/202

Bibliographic Details

Title: Kalman Filtering: with Real-Time ...

Publisher: Springer

Publication Date: 1991

Binding: Soft cover

Condition: Sehr gut

Edition: 2nd Edition

About this title

Synopsis:

This book presents a thorough discussion of the mathematical theory of Kalman filtering. The filtering equations are derived in a series of elementary steps enabling the optimality of the process to be understood. It provides a comprehensive treatment of various major topics in Kalman-filtering theory, including uncorrelated and correlated noise, colored noise, steady-state theory, nonlinear systems, systems identification, numerical algorithms, and real-time applications. A series of problems for the student, together with a complete set of solutions, are also included. The style of the book is informal, and the mathematics elementary but rigorous, making it accessible to all those with a minimal knowledge of linear algebra and systems theory. In this second edition, in addition to some minor corrections and up-dating, the section on real-time system identification has been expanded and a brief introduction to wavelet analysis included.

From the Back Cover:

This new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant systems, extended Kalman filtering for nonlinear systems, interval Kalman filtering for uncertain systems, and wavelet Kalman filtering for multiresolution analysis of random signals. Most filtering algorithms are illustrated by using simplified radar tracking examples. The style of the book is informal, and the mathematics is elementary but rigorous. The text is self-contained, suitable for self-study, and accessible to all readers with a minimum knowledge of linear algebra, probability theory, and system engineering. Over 100 exercises and problems with solutions help deepen the knowledge. This new edition has a new chapter on filtering communication networks and data processing, together with new exercises and new real-time applications.